from iiboost import Booster
from sklearn.externals import joblib # to load data
# to show something
import matplotlib.pyplot as plt
# load data
gt = joblib.load("../../testData/gt.jlb")
img = joblib.load("../../testData/img.jlb")
model = Booster()
# Train: note that we pass a list of stacks
model.train([img], [gt], numStumps=100, debugOutput=True)
pred = model.predict(img)
# show image & prediction side by side
plt.ion()
plt.figure()
plt.subplot(1, 2, 1)
plt.imshow(img[:, :, 10], cmap="gray")
plt.title("Click on the image to exit")
plt.subplot(1, 2, 2)
plt.imshow(pred[:, :, 10], cmap="gray")
plt.title("Click on the image to exit")
